Recommendation based on dominant emotion using user-specific baseline emotion and emotion analysis

ABSTRACT

Electronic apparatus that stores user information received from a plurality of sensor that tracks user activities of a user over a specified time period. The electronic apparatus includes circuitry that detects a baseline emotion of the user based on the user information. The circuitry detects a dominant emotion of the user based on a change in an emotional characteristic of the user and the detected baseline emotion. The circuitry further recommends content and an emotional storyboard to the user based on specified emotion associated with the content, the baseline emotion, and the dominant emotion. The recommended content and the emotional storyboard is to induce a change in an emotional type of the dominant emotion from a negative emotional type to a positive emotional type.

CROSS-REFERENCE TO RELATED APPLICATIONS/INCORPORATION BY REFERENCE

None.

FIELD

Various embodiments of the disclosure relate to timeline based emotiontracking and analysis technologies and content recommendationtechnologies. More specifically, various embodiments of the disclosurerelate to an electronic apparatus and a method to recommend a specificcontent based on detection and analysis of dominant emotion anduser-specific baseline emotion.

BACKGROUND

Recent advancement in the field of human emotion detection have led todevelopment of various technologies to monitor emotion of a user.Different users may respond differently to a given situation. Further,it is observed that an emotion is manifested on a user's face, behavior,or in presence of another individual in a given situation, is alsospecific for a specific user. Existing technology to detect emotionstypically set blanket emotion detection rules that are almost the samefor all users, and are thus not effective and accurate enough in emotiontracking for different users. Further, certain conventional solutions,which continuously monitor the emotion of a specific user, may lack anintelligent or enabling technology to improve an emotional state of theuser. Thus, an advanced system may be desired to monitor emotion stateof the user in detail, and provide technological solutions to improvethe emotional state as well as health state specific to the user.

Further limitations and disadvantages of conventional and traditionalapproaches will become apparent to one of skill in the art, throughcomparison of described systems with some aspects of the presentdisclosure, as set forth in the remainder of the present application andwith reference to the drawings.

SUMMARY

An electronic apparatus and method to provide recommendation based ondominant emotion using user-specific baseline emotion and emotionanalysis is provided substantially as shown in, and/or described inconnection with, at least one of the figures, as set forth morecompletely in the claims.

These and other features and advantages of the present disclosure may beappreciated from a review of the following detailed description of thepresent disclosure, along with the accompanying figures in which likereference numerals refer to like parts throughout.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates an exemplary networkenvironment for generating an emotional storyboard and recommendingcontent or action, in accordance with an embodiment of the disclosure.

FIG. 2 is a block diagram that illustrates an exemplary electronicapparatus for generating an emotional storyboard and recommendingcontent or action, in accordance with an embodiment of the disclosure.

FIGS. 3A and 3B, collectively, illustrate exemplary operations fordetection of baseline emotion and dominant emotion, by the electronicapparatus of FIG. 2, in accordance with an embodiment of the disclosure.

FIG. 4 illustrates exemplary operations to detect triggers in detecteddominant emotion, by the electronic apparatus of FIG. 2, in accordancewith an embodiment of the disclosure.

FIGS. 5A and 5B, collectively, illustrates exemplary operations topredict emotions for user, by the electronic apparatus of FIG. 2, inaccordance with an embodiment of the disclosure.

FIG. 6 illustrates an exemplary first user interface to displayrecommended content or action, in accordance with an embodiment of thedisclosure.

FIGS. 7A, 7B, and 7C, collectively, illustrate exemplary second userinterface to display an emotional storyboard, in accordance with anembodiment of the disclosure.

FIG. 8 illustrates exemplary third user interface to display aregistration process of a user, in accordance with an embodiment of thedisclosure.

FIGS. 9A and 9B collectively depict a flowchart that illustratesexemplary operations for generating an emotional storyboard andrecommending content or action, in accordance with an embodiment of thedisclosure.

DETAILED DESCRIPTION

The following described implementations may be found in the disclosedsystem to recommend content or action based on dominant emotiondetection and user-specific baseline emotion. The disclosed systemincludes an electronic apparatus that processes user information over aspecified time period to create a detailed emotional timeline andrecommend appropriate content or action to improve an emotional state ofthe user. The disclosed electronic apparatus provides a mechanism thatsupports identifying a baseline emotion of a user, monitors keyemotions, and changes in emotions of users over time. The disclosedelectronic apparatus generates an insightful analysis as an emotionaljourney for a particular user so that the user is able to assess notonly the moments triggering emotional peaks but also relatedrecommendations to improve the emotional state of the user over time.Emotion triangle technology is also disclosed that involves identifyingan emotion of the content or action recommended, emotion of the user,and the emotion, which the content or the action can invoke in a viewer.The electronic apparatus further analyses and determines dominantemotion of a user by baselining (i.e., user-specific baseline emotiondetermination) the user's emotion and identifying certain peaks in theemotion changes along with an intensity of the user's emotion. Thisenables the electronic apparatus to output a highly effective content oraction recommendations and assists users to achieve and manage a betteremotional health and reduces impact of negative emotions. The disclosedelectronic apparatus assists different user to be conscious of their ownemotional triggers and emotional peaks in a specific context or a givensituation that may be specific to a user.

FIG. 1 is a block diagram that illustrates an exemplary networkenvironment to generate an emotional storyboard and recommend content oraction, in accordance with an embodiment of the disclosure. Withreference to FIG. 1, there is shown a network environment 100. Thenetwork environment 100 may include an electronic apparatus 102, acommunication network 104, and a plurality of sensors 106, a server 108,and a multimedia content source 110. The electronic apparatus 102 may becommunicatively coupled to the plurality of sensors 106, the server 108,and the multimedia content source 110 via the communication network 104.There is further shown a user 112 associated with the electronicapparatus 102 in a three-dimensional (3D) space 114.

The electronic apparatus 102 may include suitable logic, circuitry, andinterfaces that may be configured to capture user information of theuser 112 from the plurality of sensors 106 over a specified time period.The electronic apparatus 102 may be further configured to analyze theuser information to generate an emotional storyboard of the user'semotion and recommend content or action to the user 112. The electronicapparatus 102 may be configured to receive the recommended content orinformation with respect to action from the multimedia content source110 through the communication network 104. In accordance with anembodiment, the electronic apparatus 102, the plurality of sensors 106,and the user 112 may be present in the 3D space 114. Examples of theelectronic apparatus 102 may include a health monitoring system, asurveillance device, an electronic voice assistant, an audio-visualvirtual assistant, a wearable device, an artificial intelligence (AI)system, a mobile phone, an audio-video reproduction apparatus, aspecial-purpose device, a laptop computer, a video-conferencing system,a computing device, a gaming device, a mainframe machine, a server, acomputer work-station, a consumer electronic (CE) device, or a mediaprocessing system.

The communication network 104 may include a communication medium throughwhich the electronic apparatus 102 may be communicatively coupled to theplurality of sensors 106, the server 108, and the multimedia contentsource 110. Examples of the communication network 104 may include, butare not limited to, the Internet, a cloud network, a Wireless Fidelity(Wi-Fi) network, a Personal Area Network (PAN), a Local Area Network(LAN), or a Metropolitan Area Network (MAN). Various devices in thenetwork environment 100 may be configured to connect to thecommunication network 104, in accordance with various wired and wirelesscommunication protocols. Examples of such wired and wirelesscommunication protocols may include, but are not limited to, at leastone of a Transmission Control Protocol and Internet Protocol (TCP/IP),User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), FileTransfer Protocol (FTP), Zig Bee, EDGE, IEEE 802.11, lightfidelity(Li-Fi), 802.16, IEEE 802.11s, IEEE 802.11g, multi-hopcommunication, device to device communication, cellular communicationprotocols, and Bluetooth (BT) communication protocols.

The plurality of sensors 106 may include suitable logic, circuitry, andinterface that may be configured to capture the user information of theuser 112. The user information may correspond to emotional data of theuser 112. The plurality of sensors 106 may include, but are not limitedto a biometric sensor 106A, an audio sensor 106B, and an image capturingdevice 106C. The biometric sensor 106A may be configured to capturebiometric data, as the user information, of the user 112. Examples ofthe biometric sensor 106A may include, but are not limited to, a pulserate sensor, a breath rate sensor, a body temperature sensor, aheartbeat sensor, a blood-flow sensor, an IoT sensor or a skinconductance sensor, or other specialized sensors to measure differentemotions aroused in the user 112. In some embodiments, the biometricsensor 106A may be non-invasively attached to body of the user 112. Insome embodiments, the biometric sensor 106A may be invasively implantedinside the body of the user 112. In some embodiments, the biometricsensor 106A may be installed in the 3D space 114, to collectivelymonitor the biometric data of the user 112.

The audio sensor 106B may be configured to capture voice data of theuser 112 over the specified time period. The captured voice data may bea part of the user information. The audio sensor 106B may be positionedon the body of the user 112 or may be positioned at a plurality oflocations within the 3D space 114. Examples of the audio sensor 106B mayinclude, but are not limited to, a microphone or other audio capturingdevice known in the art.

The image capturing device 106C may be configured to capture a pluralityof images of the user 112 over the specified time period. The capturedplurality of images may be utilized to determine a facial expression ofthe user 112 based on which an emotional state of the user 112 may bedetermined for the specified time period. The image capturing device106C may be positioned at any location in the 3D space 114 to capturethe plurality of image frames of the user 112. In accordance with anembodiment, the position of the image capturing device 106C may bechangeable. Examples of the image capturing device 106C may include, butare not limited to, an image sensor, a wide-angle camera, an actioncamera, a closed-circuit television (CCTV) camera, a camcorder, atime-of-flight camera (TOF camera), a night-vision camera such asInfrared (IR) camera, and/or other image capturing devices. Inaccordance with an embodiment, the plurality of sensors 106 may beintegrated in the electronic apparatus 102. In accordance with anembodiment, the image capturing device 106C may comprise a GlobalPositioning System (GPS) configured to detect current location of theelectronic apparatus 102. The electronic apparatus 102 may be configuredto identify environmental conditions (for example temperature, humidity,rainfall) around the electronic apparatus 102 or the user 112 based onthe detected current location. In accordance with an embodiment, theelectronic apparatus 102 may be configured to receive informationrelated to the environmental conditions from the server 108 based on thedetected current location.

The server 108 may include suitable logic, circuitry, and interfacesthat may be configured to store user information of the user 112. Theuser information may include user-profile information, user-contentpreference information, an event calendar, and past emotionalinformation of the user 112. In accordance with an embodiment, theserver 108 may be configured to store and continuously update anemotional storyboard of the user 112 generated in past. In accordancewith an embodiment, the server 108 may be configured to provide thestored information related to the user 112, and stored emotionalstoryboard to the electronic apparatus 102 through the communicationnetwork 104. In some embodiments, the server 108 may be implemented as acloud server, which may be utilized to execute aforementioned operationsof the server 108 through web applications, cloud applications, HTTPrequests, repository operations, file transfer, gaming operations, andthe like. Other examples of the server include, but are not limited to adatabase server, a file server, a web server, an application server, amainframe server, a cloud server, or other types of server.

The multimedia content source 110 may include suitable logic, circuitry,and interfaces that may be configured to store multimedia content.Examples of the multimedia content may include, but are not limited to,audio content, video content, animation content, and/or interactivecontent. The interactive content may comprise, but is not limited toaugmented reality (AR), virtual reality (VR), mixed reality (MR), orextended reality (XR). In accordance with an embodiment, the multimediacontent source 110 may be configured to provide the stored multimediacontent to the electronic apparatus 102 via the communication network104 based on a request for content received from the electronicapparatus 102 or the server 108. In some embodiments, the multimediacontent source 110 may be a server which may be configured to store themultimedia content. In some embodiments, the multimedia content source110 may be implemented as a cloud server, which may be utilized toexecute aforementioned operations of the multimedia content source 110through web applications, cloud applications, HTTP requests, repositoryoperations, file transfer, gaming operations, and the like. Otherexamples of the server include, but are not limited to a databaseserver, a file server, a web server, an application server, a mainframeserver, a cloud server, or other types of server.

The 3D space 114 may refer to a 3D area in which the electronicapparatus 102, user 112 and the plurality of sensors 106 are present.Examples of the 3D space 114 may include, but are not limited to, aphysical space within room or a building (such as an enclosedresidential space, a movie theater, a conference area, and the like), ora combination of the open space and built architectures (e.g., astadium, an outdoor musical event, a park, a playground, and the like).

In operation, the plurality of sensors 106 may be configured to trackuser activities of the user 112 over a specified period of time (such asin hours, days, weeks, months or years). In accordance with anembodiment, the electronic apparatus 102 may be configured to receivethe user information from the plurality of sensors 106 via thecommunication network 104. The user information may include thebiometric data, voice data, the plurality of images (including facialexpression) of the user 112, the current location of the electronicapparatus 102, and the information related to environmental conditionsaround the electronic apparatus 102 or the user 112.

In accordance with an embodiment, the electronic apparatus 102 may beconfigured to store the user information of the user 112 in theelectronic apparatus 102. The electronic apparatus 102 may be furtherconfigured extract (or detect) a baseline emotion of the user 112 basedon the user information. The baseline emotion may be an initial baselineemotion which may correspond to a neutral emotion of the user 112. Theneutral emotion may be further updated by the electronic apparatus 102over a first time period in the specified time period to obtain theactual baseline emotion of the user 112. In some embodiments, thebaseline emotion of the user 112 may correspond to a natural or usualemotion (or behavior) of the user 112. In accordance with an embodiment,the electronic apparatus 102 may be configured to detect the baselineemotion based on the plurality of categories of user emotions stored inthe electronic apparatus 102. The plurality of categories of useremotions may include, but are not limited to, a happy emotion, a sademotion, an angry emotion, a calm emotion, a fear emotion, a neutralemotion, an excited emotion, a confused emotion, a stressed emotion, adisgusted emotion, a surprised emotion, an excitement emotion, or ascared emotion. In some embodiments, the plurality of categories of useremotions may be identified based on, but are not limited to, humanemotions as mentioned in Plutchik wheel of emotions, Lövheim cube ofemotion, PAD emotional state model, Positive activation-negativeactivation (PANA) model, circumplex model, vector model, Plutchik'swheel in Venn format, Parrott's emotions or the Hourglass of Emotions.In accordance with an embodiment, the electronic apparatus 102 may beconfigured to receive the plurality of categories of user emotions fromthe server 108 via the communication network 104.

The electronic apparatus 102 may be further configured to monitor anddetect a change in an emotion characteristic of the user 112 over asecond time period in the specified time period based on the userinformation. The second time period may be different from the first timeperiod. For example, after the baseline emotion of a specific user isknown, then the change in the emotion characteristics may be detectedeffectively. If the change is detected before the baseline emotiondetection, then the detected change may be erroneous. The emotionalcharacteristic of the user 112 may correspond to a category of emotionin the plurality of categories of user emotions. In accordance with anembodiment, the electronic apparatus 102 may be configured to detectintensity levels of the emotional characteristic of the user 112. Theelectronic apparatus 102 may be further configured to detect anemotional peak of the detected intensity levels in the emotioncharacteristic of the user 112 based on a set threshold intensity of theemotional characteristic. The electronic apparatus 102 may be furtherconfigured to determine a dominant emotion of the user 112 based on thedetected change in the emotional characteristic of the user 112, thedetected emotional peak, and the baseline emotion. In accordance with anembodiment, the electronic apparatus 102 may be configured to update thebaseline emotion (e.g. which may be initially neutral orself-information provided by the user 112) with the detected dominantemotion. The detection of the dominant emotion of the user 112 based onthe user information (received from the plurality of sensor 106) may bedescribed in detail, for example, in FIGS. 3A to 3B.

In accordance with an embodiment, the electronic apparatus 102 may befurther configured to identify an emotional type of the determineddominant emotion. The emotional type is one of a positive emotional type(such as happy emotion) or a negative emotional type (such as sad orangry emotion). The electronic apparatus 102 may be further configuredto generate deductive information based on an association of theidentified emotional type of the dominant emotion, the determineddominant emotion of the first user, the first change in the emotionalcharacteristic of the first user, and the detected baseline emotion. Thedeductive information may be an insight or new supplemental informationnot present previously in the electronic apparatus 102, where thedeductive information is used as control instructions for variousoperations. For example, the electronic apparatus 102 may be configuredto identify first content or action based on a specified emotionassociated with the first content or action, and the generated deductiveinformation. In some embodiments, the deductive information may begenerated based on artificial intelligence (AI) and its variants appliedon the user information, the identified emotional type of the dominantemotion, the determined dominant emotion of the first user, the firstchange in the emotional characteristic of the first user, and thedetected baseline emotion to deduce a relationship among different datapoints and find insights. The first content may include, but are notlimited to, audio content, video content, image content, animatedcontent, multimedia content. The action identified by the electronicapparatus 102 or recommended to the user 112 may include, but are notlimited to, an activity-to-do or place-to-visit.

In accordance with an embodiment, the electronic apparatus 102 may beconfigured to send the request for content or action to the multimediacontent source 110 for the identified first content or action via thecommunication network 104. The electronic apparatus 102 may be furtherconfigured to receive the identified first content or action from themultimedia content source 110 via the communication network 104. Inaccordance with an embodiment, the electronic apparatus 102 may befurther configured to identify the first content or action based onuser-content preference information, the event calendar, and pastemotional information of the user 112. The electronic apparatus 102 maybe configured to receive the user-content preference information and thepast emotional information of the user 112 from the server 108 via thecommunication network 104.

In accordance with an embodiment, the electronic apparatus 102 may beconfigured to identify the first content or action with an intent tochange the emotion type of the dominant emotion of the user 112 from thenegative emotional type to the positive emotional type. The electronicapparatus 102 may be configured to control output of the identifiedfirst content or action to the user 112 based on a specified emotionassociated with the first content or action and the generated deductiveinformation such that the emotional type of the dominant emotion isinducible to the positive emotional type from the negative emotionaltype. The output of the identified first content or action may becontrolled on a display screen or the audio output device for userconsumption (e.g., of the user 112). In some embodiment, the output ofthe first content or action on the display screen may be a haptic outputor a virtual reality (VR) output. The output of the first content oraction may improve current health status of the user 112. In accordancewith an embodiment, the electronic apparatus 102 may be configured toanalyze the emotional characteristic of the user 112 after the output ofthe first content or action to determine the emotion manifested in theuser 112 based on the consumption of the first content or execution ofthe action.

The electronic apparatus 102 may be configured to store the emotions ofthe user 112 captured over the specified time period and generate adetailed emotional storyboard of the user 112. The emotional storyboardmay include an emotional timeline of the user 112. The electronicapparatus 102 may be configured to output the generated emotionalstoryboard to the user 112 through the display screen and AR/VR mediums.A graphical representation of the generated emotional storyboard isdescribed in detail, in FIGS. 7A to 7C. In some embodiments, theemotional storyboard may include information related different triggerswhich would have caused the change in the emotional characteristic ofthe user 112 over the specified time period. The triggers may include,but are not limited to, second content the user 112 may be viewing (orlistening) or action the user 112 may be performing during the specifiedtime period, events associated with the user 112 during the specifiedtime period, or related people and surrounding environment around theuser 112 that may influence the user 112 during the specified timeperiod. The surrounding environment may be detected based on theinformation related environmental conditions around the electronicapparatus or the user 112. Information related to the different triggersmay be described in detail, for example in FIG. 5. Thus, the disclosedelectronic apparatus 102 may perform the detailed analysis of the userinformation of the user 112 for the specified time period which may varyfrom certain days to months or years. The detailed analysis of the userinformation and output of the dominant emotion (with relevant triggers)through the generated emotional storyboard may facilitate the user 112to accurately understand the user's emotional patterns or changesspecific to the user 112 over the specified time period. Further,accurate recommendation of the first content or action by the electronicapparatus 102 based on the detailed analysis of the user information andthe generated emotional storyboard may further ensure an improvement inthe emotional quotient of the user 112. Such improvement in theemotional quotient may further assist the user 112 to improve healthstatus and fitness over time.

FIG. 2 is a block diagram that illustrates an exemplary electronicapparatus for generating an emotional storyboard and recommendingcontent or action, in accordance with an embodiment of the disclosure.FIG. 2 is explained in conjunction with elements from FIG. 1. Withreference to FIG. 2, there is shown a block diagram of the electronicapparatus 102. The electronic apparatus 102 may include circuitry 202that may include a processor 204, an emotion recognition and predictionengine 206, and an emotional storyboard generator 208. There is furthershown a network interface 210, a memory 212, an Input/output (I/O)device 214, and the plurality of sensors 106 of FIG. 1. The I/O device214 may include a display device 214A. The plurality of sensors 106 mayinclude the biometric sensor 106A, the audio sensor 106B, and the imagecapturing device 106C. The circuitry 202 may be communicatively coupledwith the network interface 210, the memory 212, the I/O device 214, andthe plurality of sensors 106, via a set of communication ports/channels.

The processor 204 may include suitable logic, circuitry, and interfacesthat may be configured to execute a set of instructions stored in thememory 212. The processor 204 may be configured to read the userinformation stored in the memory 212. In some embodiments, the processor204 may be configured to receive the user information from the pluralityof sensors 106. In some embodiments, the processor 204 may be configuredto control the plurality of sensors 106 to track the user activities andprovide the user information. The processor 204 may be furtherconfigured to receive user emotions associated with a plurality ofcategories of user emotions, the user-content preference information andthe past emotional information of the user 112 from the server 108 viathe network interface 210. The processor 204 may be further configuredto receive the first content or the information related to the actionfrom the multimedia content source 110 via the network interface 210.The processor 204 may be further configured to output the received firstcontent or the information related to the action to the user 112 throughthe I/O device 214. In some embodiments, the processor 204 may beconfigured to request the multimedia content server 110 to streamcontent (such as the first content or the information related to theaction) in real time to a device associated with the user 112. In someembodiments, the processor 204 may be embedded with the plurality ofsensors 106 such as e-sensors. The processor 204 may be implementedbased on a number of processor technologies known in the art. Examplesof the processor 204 may include, but are not limited to, a GraphicalProcessing Unit (GPU), a Central Processing Unit (CPU), an x86-basedprocessor, an x64-based processor, a Reduced Instruction Set Computing(RISC) processor, an Application-Specific Integrated Circuit (ASIC)processor, a Complex Instruction Set Computing (CISC) processor, lowpower deep neural network (DNN).

The emotion recognition and prediction engine 206 may include suitablelogic, circuitry, and/or interfaces that may be configured to receivethe user information of the user 112 from the processor 204. The emotionrecognition and prediction engine 206 may be further configured todetect the emotions of the user 112 (such as happy, sad, angry, neutralor other possible emotions) based on the user information of the user112 and the plurality of categories of user emotions. The emotionrecognition and prediction engine 206 may be further configured todetect the baseline emotion of the user 112 for the specified timeperiod. In accordance with an embodiment, the emotion recognition andprediction engine 206 may be further configured to detect the change inthe emotional characteristic of the user 112. For example, the emotionrecognition and prediction engine 206 may be further configured todetect a change in the facial expression or a change in breathing rateto detect the change in the emotional characteristic of the user 112.The emotion recognition and prediction engine 206 may be furtherconfigured to detect a change in the intensity levels of the emotionalcharacteristic of the user 112 and set a threshold intensity of theemotional characteristic. The emotion recognition and prediction engine206 may be further configured to detect the emotional peak of theintensity levels of the emotional characteristic based on the setthreshold intensity. The emotion recognition and prediction engine 206may be further configured to detect the dominant emotion as the changedemotion of the user 112 based on the detected emotional peak or thedetected change in the emotional characteristic of the user 112.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to predict the emotion of the user112 based the user-content preference information and the past emotionalinformation of the user 112 associated with the user-content preferenceinformation. Examples of implementations of the emotion recognition andprediction engine 206 may be a specialized circuitry, an inferenceengine circuitry, a neural network circuitry, a co-processor, a GraphicsProcessing Unit (GPU), a Reduced Instruction Set Computing (RISC)processor, an Application-Specific Integrated Circuit (ASIC) processor,a Complex Instruction Set Computing (CISC) processor, a microcontroller,a central processing unit (CPU), or other control circuits.

The emotional storyboard generator 208 may include suitable logic,circuitry, and/or interfaces that may be configured to receive the userinformation from the processor 204. The emotional storyboard generator208 may be further configured to receive the detected emotions of theuser 112, the baseline emotion, the detected dominant emotion and thetriggers for change in the baseline emotion from the emotion recognitionand prediction engine 206. The emotional storyboard generator 208 may befurther configured to generate the emotional storyboard of the user 112for the specified time period. The emotional storyboard may be anemotional timeline of the user's emotion for the specified time period.In accordance with an embodiment, the emotional storyboard may includethe user information, the triggers for the change in the emotionalcharacteristic of the user 112 in the specified time period. Examples ofimplementations of the emotional storyboard generator 208 may be aspecialized circuitry, a Graphics Processing Unit (GPU), a co-processor,a Reduced Instruction Set Computing (RISC) processor, anApplication-Specific Integrated Circuit (ASIC) processor, a ComplexInstruction Set Computing (CISC) processor, a microcontroller, a centralprocessing unit (CPU), or other control circuits.

The network interface 210 may include suitable logic, circuitry, andinterfaces that may be configured to establish communication between theelectronic apparatus 102, the server 108, and the multimedia contentsource 110, via the communication network 104. The network interface 210may be implemented by use of various known technologies to support wiredor wireless communication of the electronic apparatus 102 with thecommunication network 104. The network interface 210 may include, but isnot limited to, an antenna, a radio frequency (RF) transceiver, one ormore amplifiers, a tuner, one or more oscillators, a digital signalprocessor, a coder-decoder (CODEC) chipset, and a local buffer. Inaccordance with an embodiment, the network interface 210 may furtherinclude a subscriber identity module (SIM) card.

The memory 212 may include suitable logic, circuitry, and interfacesthat may be configured to store a set of instructions executable by theprocessor 204. The memory 212 may be configured to store the userinformation captured by the plurality of sensors 106. In someembodiments, the memory 212 may be configured to store the plurality ofcategories of user emotions and their corresponding values of emotionalcharacteristic. In some embodiments, the memory 212 may be configured tostore the user-content preference information, the event calendar, theinformation related environmental conditions, and the past emotionalinformation of the user 112. In some embodiments, the memory 212 may beconfigured to store a plurality of content items, such as the firstcontent or the information related to the action, received from themultimedia content source 110 that to be recommended to the user 112.Examples of implementation of the memory 212 may include, but are notlimited to, Random Access Memory (RAM), Read Only Memory (ROM),Electrically Erasable Programmable Read-Only Memory (EEPROM), Hard DiskDrive (HDD), a Solid-State Drive (SSD), a CPU cache, or a Secure Digital(SD) card.

The I/O device 214 may include suitable logic, circuitry, and interfacesthat may be configured to provide an I/O channel/interface between theuser 112 and the different operational components of the electronicapparatus 102. The I/O device 214 may receive an input from the user 112and present an output based on the provided input from the user 112. TheI/O device 214 may include various input and output ports to connectvarious other I/O devices that may communicate with differentoperational components of the electronic apparatus 102. Examples of theinput device may include, but are not limited to, a touch screen, akeyboard/keypad, a set of buttons, a mouse, a joystick, a microphone,and an image-capture device. Examples of the output device may include,but are not limited to, a display (for example, the display device214A), a speaker, and a haptic or any sensory output device.

The display device 214A may include suitable logic, circuitry,interfaces that may be configured to render an application interface atthe display device 214A, to display the emotional storyboard and therecommended first content or the information related to the action tothe user 112 operating the electronic apparatus 102. The display device214A may be realized through several known technologies such as, but notlimited to, at least one of a Liquid Crystal Display (LCD) display, aLight Emitting Diode (LED) display, a plasma display, and an Organic LED(OLED) display technology, and other display. In accordance with anembodiment, the display device 214A may refer to a display screen ofsmart-glass device that are compatible with the AR, VR, MR, and XRtechnologies, a see-through display, a projection-based display, anelectro-chromic display, and a transparent display.

The functions or operations executed by the electronic apparatus 102, asdescribed in FIG. 1, may be performed by the circuitry 202, such as theprocessor 204, the emotion recognition and prediction engine 206, andthe emotional storyboard generator 208, which are further described, forexample, in the FIGS. 3A, 3B, 4, 5A, 5B, 6, and 7A to 7C.

FIGS. 3A and 3B, collectively, illustrate exemplary operations fordetection of baseline emotion and dominant emotion, in accordance withan embodiment of the disclosure. FIG. 3A is explained in conjunctionwith elements from FIGS. 1 and 2. With reference to FIG. 3A, there isshown a plurality of image frames 302. The plurality of image frames 302may include image frames 302A to 302G captured by the image capturingdevice 106C over the specified time period. The image frames 302A to302G may include an image 304 of the user 112. In some embodiments, theimage frames 302A to 302G may include the facial expression in the userinformation of the user 112. The facial expression may indicate one ormore motions or positions of muscles of a face of the user 112, wherethe facial expressions may manifest an emotion. The muscles of the facemay move the skin of the user 112, may create facial lines/folds, or maycause the movement of facial features, such as mouth, head, nose, eye,eyebrows of the user 112. In accordance with an embodiment, the imageframes 302A to 302G are consecutively captured by the image capturingdevice 106C over the specified time period.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the emotion of the user 112 ineach of the image frames 302A to 302G captured over the specified timeperiod. The specified time period may in minutes, hours, days, weeks,months, or years. In accordance with an embodiment, the electronicapparatus 102 may be configured to receive a user input from the user112 to set the specified time period to track the user activities (orthe user information). The emotion recognition and prediction engine 206may be configured to determine the facial expressions of the user 112and detect emotions based on the user information (such as thedetermined facial expressions) and the stored plurality of categories ofuser emotions. The categories of the user emotions may include, but arenot limited to, a happy emotion, a sad emotion, an angry emotion, a calmemotion, a fear emotion, a neutral emotion, an excited emotion, aconfused emotion, a stressed emotion, a disgusted emotion, a surprisedemotion, an excitement emotion, a scared emotion, or a mixed emotion. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to match the detected facial expressionwith each of the plurality of categories of user emotions to determinethe emotion of the user 112 in each of the image frames 302A to 302G.For example, in a set of image frames 302A to 302E, the detected emotionof the user 112 may be the happy emotion. The user 112 may be happy overthe first time period in the specified time period. The emotionrecognition and prediction engine 206 may be configured to set thebaseline emotion of the user 112 as happy based on the detected emotionof the user 112 for the first time period. In some embodiments, thebaseline emotion of the user 112 may correspond to natural or generalemotion (or behavior) of the user 112. Although a number of image frames(e.g., the set of image frames 302A to 302E) are shown in the FIG. 3A,to detect a baseline emotion, image analysis by the emotion recognitionand prediction engine 206 for a longer period of time, for example forone or more weeks, may provide more accurate understanding and detectionof the baseline emotion.

In accordance with an embodiment, the plurality of categories of useremotions may include different values of biometric or voice dataassociated with each category of the plurality of categories of useremotions. For example, a value of heartbeat above 100 bpm (beats perminute) of the user 112 may be associated with the fear emotion orexcitement emotion of the user 112. A volume of voice above 75 decibels(dB) may be associated with the anger emotion of the user 112. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to detect the emotion of the user112 based on comparison between different values in the user informationcaptured from the plurality of sensors 106 and the values of biometricor voice data included with each category of the plurality of categoriesof user emotions.

The emotion recognition and prediction engine 206 may be furtherconfigured to detect the change in the emotional characteristic of theuser 112. The emotional characteristic may indicate the detected emotionof the user 112 in each of the image frames 302A to 302G. For example, afirst image frame 302E and a second image frame 302F of the image frames302A to 302G may indicate the change in the emotional characteristic ofthe user 112 from the happy emotion to the neutral emotion. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to detect a subsequent image frame302G which is subsequent to the changed second image frame 302F toconfirm the change in the emotional characteristic of the user 112. Theemotion recognition and prediction engine 206 may be further configuredto detect the change in the emotional characteristic of the user 112over a second time period (different from the first time period). Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to detect the dominant emotion ofthe user, as the neutral emotion, based on the detected change in theemotional characteristic of the user 112 over the second time period. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to update (or calibrate) thebaseline emotion based on the dominant emotion. In accordance with anembodiment, the user information of the user 112 may include thebiometric data or the voice data captured from the plurality of sensors106. The emotion recognition and prediction engine 206 may be configuredto detect the baseline emotion and the dominant emotion of the user 112over the specified time period based on the captured biometric data orthe voice data of the user 112. Thus, the electronic apparatus 102 mayprovide accurate detection of the emotional characteristics of the user112 based on the combination of the biometric data, the voice data andthe plurality of images in the user information of the user 112.

With reference to FIG. 3B, there is shown a graphical representation 306of intensity levels of the emotion of the user 112 for a time period(e.g., 12 hours from 12 am to 12 pm). The graphical representation 306of the emotion may indicate the different intensity levels of aparticular emotion during the time period. For example, the intensitylevels of the emotion may vary from a scale of “1 to 10”. In accordancewith an embodiment, the intensity levels of each emotion experienced bythe user 112 may be divided into three categories as a high intensity308, a medium intensity 310, and a low intensity 312. The low intensity312 may correspond to “1 to 3” intensity level, the medium intensity 310may correspond to “4 to 6” intensity level, and the high intensity 312may correspond to “7 to 10” intensity levels.

The graphical representation 306 may further indicate an emotional peak314 for the emotion of the user 112 during the time period (e.g., 12hours duration). The emotional peak may be a highest intensity level ofthe emotion during the time period. In accordance with an embodiment,the emotional peak 314 may correspond to the change in the intensitylevels of the baseline emotion or the emotion characteristic of the user112 over the time period. The emotion recognition and prediction engine206 may be configured to dynamically or statically set the thresholdintensity for the emotional peak. The emotion recognition and predictionengine 206 may be configured to dynamically or statically set thethreshold intensity for the emotional peak based on a range of theintensity levels over the time period. For example, the emotionrecognition and prediction engine 206 may be configured to set thethreshold intensity at a low level of 2, if the intensity levels of thebaseline emotion is in range of 1 to 3 over the time period. Further,the emotion recognition and prediction engine 206 may be configured toset the threshold intensity at a high level of 8, if the intensity levelof the baseline emotion is in a range of 7 to 10 over the time period.With reference to the graphical representation 306, the user 112achieved the emotional peak 314 at 7 pm. This type of analysis andrepresentation in emotion intensity levels assists the user 112 to beconscious of their own emotional triggers and emotional peaks in aspecific context or a given situation that may be specific to a user,such as the user 112.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the emotional peak 314 based onthe threshold intensity. In accordance with an embodiment, the emotionrecognition and prediction engine 206 may be configured to detect thechange in the emotional characteristic of the user 112 based on thedetected emotional peak 314. In accordance with an embodiment, theemotion recognition and prediction engine 206 may be configured todetect the dominant emotion of the user 112 based on the detectedemotional peak 314 of the time period.

FIG. 4 illustrates exemplary operations for detecting triggers indetected dominant emotion, by the electronic apparatus of FIG. 2, inaccordance with an embodiment of the disclosure. FIG. 4 is explained inconjunction with elements from FIGS. 1, 2, 3A, and 3B. With reference toFIG. 4, there is shown a plurality of image frames 402 that includes,for example, image frames 402A to 402H captured by the image capturingdevice 106C over the specified time period. The plurality of imageframes 402 in FIG. 4 may be similar to the plurality of image frames 302in FIG. 3. The image frames 402A to 402H may include user representation404 (or detected emotion) of the user 112. In some embodiments, theimage frames 402A to 402H may also include information related tosurroundings of the user 112 during the specified time period of captureof the user information. The information related to the surroundings mayinclude information related events (such as dance party, musical event,birthday celebration, official meeting, or examination hall) occurrednear the user 112, second content the user 112 may be viewing orlistening or information about another user in proximity to the user 112(e.g., a family member, a friend, or a pet who may have an influencerelated to emotion of the user 112). Such information related to thesurrounding of the user 112 may change the facial expression (or theemotion characteristic) of the user 112 and may be referred as thetriggers related to the user 112. In some embodiments, the triggersrelated to the user 112 may include information related to environmentalconditions near the user 112, date-time information, or the currentlocation of the user 112. In some embodiments, the triggers related tothe user 112 may include information related to one or more non-livingobjects (for example, gifts, pictures, decorative items, or furnitureitems) around the user 112.

In FIG. 4, a first image frame 402A of the image frames 402A to 402H mayinclude a user representation 404 (the emotion characteristic) of theuser 112. A second image frame 402B and a third image frame 402C of theimage frames 402A to 402H may include a first person 406A in thesurroundings of the user 112. The captured facial expressions (or theemotion characteristic) of the user 112 in the first image frame 402A,the second image frame 402B and the third image frame 402C may be sameas happy (or smiling). A fourth image frame 402D of the image frames402A to 402H may include a second person 406B in the surrounding of theuser 112. The fourth image frame 402D may indicate the emotioncharacteristic of the user 112 as sad emotion. In accordance with anembodiment, the emotion recognition and prediction engine 206 may beconfigured to detect the second person 406B as the trigger in the fourthimage frame 402D which caused the change in the emotional characteristicof the user 112 from the happy emotion to the sad emotion.

A fifth image frame 402E of the image frames 402A to 402H does notinclude the first person 406A and the second person 406B. In FIG. 4, thedetected emotion of the user 112 in the fifth image frame 402E mayrepresent the happy emotion. The emotion recognition and predictionengine 206 may be configured to detect the absence of the first person406A and the second person 406B in the fifth image frame 402E as thetrigger for the positive change (sad to happy) in the emotioncharacteristic from the fourth image frame 402D to the fifth image frame402E.

In accordance with an embodiment, other factors related to the triggers(such as the environment conditions, events, location, backgroundlighting) of the user 112 may remain unchanged from the first imageframe 402A to the fifth image frame 402E. A sixth image frame 402F ofthe image frames 402A to 402H may indicate a darker background lightingin the surrounding of the user 112 as compared to other image frames.The emotion recognition and prediction engine 206 may be configured todetect the increase in an intensity level of the happy emotion in thesixth image frame 402F with the change in the background lighting (forexample as the environment conditions) around the user 112 from thefifth image frame 402E to the sixth image frame 402F. The emotionrecognition and prediction engine 206 may be configured to detect thechange in the background lighting as the trigger, which caused thechange in the intensity level of the particular emotion (say happy) ofthe user 112. This may indicate that the user 112 likes the darkbackground lighting which increased the intensity level of the happinessof the user 112. In a seventh image frame 402G of the consecutive imageframes 402A to 402H, with the change in the background lighting (saydark to bright), the emotion recognition and prediction engine 206 maybe configured to detect the change in the intensity level of the happyemotion of the user 112. In an eighth image frame 402H of the imageframes 402A to 402H may include a pet 406C in the surrounding of theuser 112. The emotion recognition and prediction engine 206 may beconfigured to detect the increase in the intensity level of the happyemotion in the eighth image frame 402H with the presence of the pet 406C(as the trigger) around the user 112 from the seventh image frame 402Gto the eighth image frame 402H.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the event (as the trigger)occurred with the user 112 during the image frames 402A to 402H todetect the change in the emotional characteristic or change in theintensity level. In accordance with an embodiment, the emotionrecognition and prediction engine 206 may be configured to detect acurrent location (as the trigger) of the user 112 to detect the changein the emotional characteristic or change in the intensity level. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the environment condition (as thetrigger) in the vicinity of the user 112 to detect the change in theemotional characteristic or change in the intensity levels (dominantemotion). Examples of the environment condition may include, but are notlimited to, temperature, rainfall, or humidity. In some embodiments, theemotion recognition and prediction engine 206 may be configured todetect the second content (as the trigger) which the user 112 might bewatching or listing or the action which the user 112 might be performingduring the capture of the image frames 402A to 402H. Thus, the emotionrecognition and prediction engine 206 may be able to correlate thedetected trigger in the plurality of image frames 402 (or the userinformation) with the detected dominant emotion (change in the emotionalcharacteristics or the change in the intensity levels) of the user 112.The electronic apparatus 102 may be configured to recommend the firstcontent or the information related to the action based on thecorrelation of the detected trigger with the dominant emotion of theuser 112. Thus, the emotion recognition and prediction engine 206 may beconfigured to generate insightful information (e.g., the deductiveinformation) to enable different users to be conscious of their ownemotional triggers and emotional peaks in a specific context or a givensituation that may be specific to a user, such as the user 112, whichmay then be used for self-corrective action and improve overallemotional health.

FIGS. 5A and 5B, collectively, illustrates exemplary operations topredict emotions for the user 112, by the electronic apparatus of FIG.2, in accordance with an embodiment of the disclosure. FIG. 5A areexplained in conjunction with elements from FIGS. 1, 2, 3A, 3B, and 4.With reference to FIG. 5A, there is shown a graphical representation 500to depict an emotional triangle. The graphical representation 500 of theemotional triangle may include a dominant emotion 502, an emotionassociated with the recommended content or action 504, and an emotion506 that the first content or the action may induce in the user 112.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the dominant emotion 502 of theuser 112. The detection of the dominant emotion of the user 112 havebeen described in detail, for example in FIGS. 3A, 3B and 4. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be further configured to detect the emotion 504associated with the first content or action output or recommended to theuser 112 based on the detected dominant emotion 502. In someembodiments, the emotion recognition and prediction engine 206 may befurther configured to retrieve the emotion 504 associated with the firstcontent or action from the server 108 via the communication network 104.The emotion recognition and prediction engine 206 may be furtherconfigured to predict the emotion 506 of the user 112 that may beinduced in the user 112 based on the recommended content or action. Forexample, when the detected dominant emotion 502 of the user 112 is thesad emotion, the electronic apparatus 102 may be configured to recommendthe first content or action associated with the emotion 504 as the happyemotion. The first content or action with the associated happy emotion504 may change the emotional characteristic of the user 112 to thepositive emotional type (say happy) from the negative emotional type(say sad). Thus, the emotion recognition and prediction engine 206 maybe configured to predict the emotion 506 as the happy emotion which maybe induced in the user 112 by the recommended first content or action.

In accordance with an embodiment, the predicted emotion 506 (PE) may bebased on the user-content preference information and the user pastemotional information received from the server 108. The user-contentpreference information may indicate which type of content (audio, video,image) may be preferred by the user 112 and may induce the positiveemotion in the user 112. The user-content preference information mayfurther indicate favorite places of the user 112 or near-by events theuser 112 might be interested in. The user-content preference informationmay include information about a role model (such as celebrity) liked bythe user 112. The processor 204 may be configured to identify the firstcontent or action for recommendation based on the information about therole model. The first content or action identified based on theinformation about the role model may include an image of the role modelwhere the image may indicate the positive behavior or the emotionalcharacteristic (say happy) of the role model. In such case, the firstcontent or action which includes the happy image of the role model mayinduce the positive emotion in the user 112. In accordance with anembodiment, the processor 204 may recommend an activity-to-do (as theaction) to the user 112 based on the behavior or the emotionalcharacteristic of the role model in the first content or action. Therecommended activity may assist the user 112 to imitate the behavior ofthe liked role model. The recommended first content or action based onthe information about the role model may assist the user 112 tounderstand different ways or solutions which helped the role model toimprove their emotional quotient in different situations.

In accordance with an embodiment, the past user emotional informationmay correspond to the user's past history with respect to therecommended first content or action and induced emotion in the user 112.The user past emotional information may include internet browsinghistory of the user 112 and frequency of viewing/listening differentcontent by the user 112. The content with high frequency may indicate ahighly preferred content by the user 112 under a given situation/emotionand may induce the positive emotion in the user 112.

In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect an actual dominant emotion (AE)that was induced in the user 112 in response to the recommended firstcontent or action. The processor 204 may be further configured to updatethe user-content preference information and the user past emotionalinformation based on the detected AE of the user 112 in response to therecommended first content or action for future predictions. Theprocessor 204 may be further configured to send the updated user-contentpreference information and the user past emotional information to theserver 108. Thus, the electronic apparatus 102 may accurately perform adetailed emotional analysis, prediction, and recommendation of contentor action to the user 112. Further, the emotional storyboard generatedbased on the detailed emotional analysis may facilitate the user 112with the detailed awareness about their emotional health and furthermotivate the user 112 to take necessary actions for the improvement oftheir emotional quotient. Thus, the present disclosure may provideseveral advantages over conventional systems.

With reference to FIG. 5B, there is shown a graphical representation 508of a user emotion 512 for different recommended content 510 to the user112. In the graphical representation 508, for the first content oraction 510A, the detected baseline emotion (BE) 512A before therecommendation of the first content or action 510A may be a neutralemotion. The emotion recognition and prediction engine 206 may beconfigured to predict that the first content or action 510A may make theuser 112 happy. The emotion recognition and prediction engine 206 may beconfigured to determine the predicted emotion (PE) 512B based on theuser-content preference information and the user past emotionalinformation. The processor 204 may be configured to detect the actualdominant emotion (AE) 512C as the happy emotion that was induced in theuser 112 in response to the recommended first content or action 510A.Further, in FIG. 5B, for the second content or action 510B, the baselineemotion (BE) 512D of the user 112 may be an angry emotion, the predictedemotion (PE) 512E may be a calm emotion, and the actual dominant emotion(AE) 512F may be the calm emotion that was induced in the user 112 inresponse to the second content or action 510B. Further, in FIG. 5B, forthe third content or action 510C, the baseline emotion (BE) 512G of theuser 112 may be an sad emotion, the predicted emotion (PE) 512H may be ahappy emotion, and the actual dominant emotion (AE) 512I may be the sademotion that was induced in the user 112 in response to the thirdcontent or action 510C. The emotion recognition and prediction engine206 may be configured to detect a difference in the predicted emotion(PE) 512H and the actual dominant emotion (AE) 512I for the thirdcontent or action 510C and update the user-content preferenceinformation and the user past emotional information of the user 112 forfuture recommendation and prediction. Therefore, the electronicapparatus 102 may be able to recommend appropriate content or action tothe user 112 to suitably convert the emotional quotient of the user 112from the negative emotional type to the positive emotional type (forexample sad to happy with the first content or action and angry to calmwith the second content or action in FIG. 5B).

FIG. 6 illustrates an exemplary first user interface to displayrecommended content or action, in accordance with an embodiment of thedisclosure. FIG. 6 is explained in conjunction with elements from FIGS.1, 2, 3A, 3B, 4, 5A and 5B. With reference to FIG. 6, there is shown anexemplary first user interface (UI) 600 which may be rendered on thedisplay device 214A. The first UI 600 includes a user image area 602,user information area 604, and a dominant emotion area 606A of the user112. There is also shown an emotional storyboard UI element 606B, and arecommendation content or action UI element 608. The recommendationcontent or action UI element 608 may include an image UI element 608A,an audio UI element 608B, a video UI element 608C, a background lightingUI element 608D, an activity UI element 608E, and places to visit UIelement 608F.

The processor 204 may be configured to display an image of the user 112(captured at the time of registration) on the user image area 602. Inaccordance with an embodiment, the processor 204 may be configured todisplay the captured user information (e.g., different emotions) of theuser 112 on the user information area 604. The display user informationmay include, but are not limited to, the biometric data, height, weight,breathing intensity, or body temperature of the user 112.

The processor 204 may be configured to display the detected dominantemotion of the user 112 at the dominant emotion area 606A. For example,the dominant emotion area 606A may display the sad emotion in case theemotion recognition and prediction engine 206 detects the emotionalcharacteristics of the user 112 as the sad emotion. The processor 204may be configured to receive a user input to display the generatedemotional storyboard through the emotional storyboard UI element 606B.For example, the user 112 may select the emotional storyboard UI element606B to display the emotional storyboard on the user 112 on the displaydevice 214A. A graphical representation of the generated emotionalstoryboard is described in detail, for example in FIGS. 7A to 7C.

In accordance with an embodiment, the processor 204 may be configured toreceive a user input as a preference for content type of the recommendedfirst content or action from the user 112. The user 112 may provide theuser input as the preference for the content type through one of theimage UI element 608A, the audio UI element 608B, the video UI element608C, the background lighting UI element 608D, the activity UI element608E, or the places to visit UI element 608F. For example, if the user112 wishes to view a movie, the user 112 may select the video UI element608C of the recommendation content or action UI element 608. Theprocessor 204 may be configured to recommend the first content as videocontent (say a specific movie) based on the selection of the video UIelement 608C by the user 112. Similarly, the processor 204 may beconfigured to control the background lighting around the user 112 basedon the selection of the background lighting UI element 608D by the user112.

In accordance with an embodiment, the processor 204 may be configured totransmit a signal to an external device based on the negative emotionaltype of the dominant emotion (for example sad, angry). The processor 204may be further configured to transmit a warning notification, as thesignal, to the external device. In accordance with an embodiment, theexternal device may be related to other people (for example parents,guardians, friends) who are in relation with the user 112.

In accordance with an embodiment, the processor 204 may be configured todetect the location of the user 112 using the GPS. The processor 204 maybe further configured to output information that recommends anactivity-to-do or information about a place-to-visit (as the action) tothe user 112 based on the detected location. In accordance with anembodiment, the processor 204 may be configured to detect health statusinformation of the user 112 based on the user information captured bythe plurality of sensors 106. The health status information may indicatea health-related issue (for example as high blood pressure, fever) withthe user 112. The processor 204 may be further configured to recommendthe first content or action to the user 112 to resolve thehealth-related issue based on the detect health status information. Insuch case, the first content or action may indicate information aboutmedicines or diagnostic centers or hospitals to the user 112.

In accordance with an embodiment, the processor 204 may be configured torecommend the first content or action based on the user-contentpreference information, the user past emotional information receivedfrom the server 108, the detected triggers which caused the change inthe emotional characteristics, and the user input (as the preference forthe content type) received from the user 112 through the first UI 600.Thus, depending on the various aforementioned factors, the electronicapparatus 102 may accurately recommend the first content or action tothe user 112 which may further ensure the improvement in the emotionhealth of the user 112 effectively. In accordance with an embodiment,the processor 204 may be configured to recommend the first content oraction as a notification to the user 112 on the I/O device 214A. Thenotification may be an image, an audio sound, a haptic output such as avibration. In some embodiments, the first UI 600 may be displayed at anexternal apparatus or an external application, via an applicationprogramming interface (API) for content or action recommendation.

FIGS. 7A, 7B, and 7C, collectively, illustrate exemplary second userinterface to display an emotional storyboard, in accordance with anembodiment of the disclosure. FIGS. 7A, 7B, and 7C are explained inconjunction with elements from FIGS. 1, 2, 3A, 3B, 4, 5A, 5B, and 6.With reference to FIG. 7A, there is shown a first emotional storyboard700 of the second user interface rendered on the display device 214A. Inaccordance with an embodiment, the processor 204 may be configured tocommunicate the generated emotional storyboard to an external displaydevice. The first emotional storyboard 700 of the second user interfacemay include time stamp information 702, trigger information 704, useremotion information 706, and other user information, such as userinformation 708.

In accordance with an embodiment, the emotional storyboard generator 208may be configured to generate the first emotional storyboard 700. Thetime stamp information 702 may indicate the specified time period overwhich the user emotion information 706 was captured from the pluralityof sensors 106. The first emotional storyboard 700 may further includethe trigger information 704 that corresponds to different triggers whichcaused the change in the emotional characteristic of the user 112.Examples of the triggers are described in detail, for example, in FIG.4. The first emotional storyboard 700 may display different triggers fordifferent time stamps in the time stamp information 702.

The first emotional storyboard 700 may further include the user emotioninformation 706. The user emotion information 706 may indicate differentemotions of the user 112 in different time stamps and with theassociated triggers. The first emotional storyboard 700 may furtherinclude the user information 708 received from the plurality of sensors106. The user information 708 may indicate the physiological andnon-physiological features (such as body temperature, blood pressure,heartbeat, etc) of the user 112 received from the plurality of sensors106 during different time period indicated by the time stamp information702. In accordance with an embodiment, the first emotional storyboard700 may include the user emotions for different time period such as foran hour, a day, a week, or a year.

In accordance with an embodiment, the first emotional storyboard 700 mayfurther include the baseline emotion and the dominant emotion detectedby the emotion recognition and prediction engine 206 over the specifiedtime period indicated by the time stamp information 702. The firstemotional storyboard 700 may further include an indicator (for exampleicon, weblink) that corresponds to the first content recommended to theuser 112 during the specified time period. In accordance with anembodiment, the emotional storyboard may further include the change inthe dominant emotion based on the recommended first content or action tothe user 112.

In accordance with an embodiment, the first emotional storyboard 700 mayfurther include an avatar of the user 112. The avatar may indicatevirtual emotions (such as a smile for happiness and tears for sadness)in the emotional storyboard. The virtual emotions may correspond to theemotions of the user 112 in response to the trigger information 704 atdifferent time period specified in the time stamp information 702.

With reference to FIG. 7B, there is shown a second emotional storyboard710 in the second user interface. The second emotional storyboard 710may indicate, for example, a day-wise distribution of various emotionsof the user 112 for a particular time period (say of one week). In someembodiments, second emotional storyboard 710 may indicate, but is notlimited to, a month-wise or year-wise distribution of various emotionsof the user 112 based on the user input received from the user 112. InFIG. 7B, the second emotional storyboard 710 may indicate the day-wisedistribution of, but is not limited to, a happy emotion 712A, a neutralemotion 712B, and a sad emotion 712C to the user 112. In someembodiments, the second emotional storyboard 710 may indicate theday-wise distribution of other plurality of categories of user emotionsas described, for example, in FIG. 1. The second emotional storyboard710 may include the emotional intensity for each day of the week whenthe user 112 had a specified emotion (such as the happy emotion 712A,the neutral emotion 712B, and the sad emotion 712C). Such detailedrepresentation in the second emotional storyboard 710 may provide theuser 112 a comprehensive view of the user's emotional health for thespecified time period. With reference to FIG. 7B, for example on Sunday(Su), the user 112 may be happy with an emotional intensity of a higherlevel (for example “9”), neutral with the emotional intensity of amedium level (for example “5”) and sad with the emotional intensity of alower level (for example “1”). In another example, on Monday (M) theuser 112 may be happy with the emotional intensity of the lower level(for example “1”), neutral with the emotional intensity of the highlevel (for example “9”) and sad with the emotional intensity of themedium level (for example “5”). Similarly, the FIG. 7B shows that theemotional characteristic and intensity of the user 112 for rest of theweek including Tuesday (Tu) Wednesday (W) Thursday (Th) Friday (F), andSaturday (Sa). In accordance with an embodiment, the electronicapparatus 102 may be configured to alter a number of category ofemotions and the specified time period in the second emotionalstoryboard 710 based on the user input received from the user 112. Inaccordance with an embodiment, the emotional storyboard generator 208may be configured to generate a storyboard similar to the secondemotional storyboard 710 that may display other variants of emotions ofthe user 112, such as anger, disgust, excitement, sorrow, fear, etc.

With reference to FIG. 7C, there is shown a third emotional storyboard714 in the second user interface. The third emotional storyboard 714 mayinclude a graphical representation of a physical activity index of theuser 112 for the specified time period (say for two weeks). Inaccordance with an embodiment, the emotional storyboard generator 208may be configured to generate the third emotional storyboard 714 toindicate the physical activity index of the user 112 based on physicalmovement of the user 112 and the user information received from theplurality of sensors 106. In accordance with an embodiment, theemotional storyboard generator 208 may be configured to detect theduration of a physical activity and a sleep cycle of the user 112 overthe specified time period to calculate the physical activity index ofthe user 112.

The third emotional storyboard 714 may indicate a comparison of twophysical activity index for different time period. A solid line mayrepresent a first physical activity index for a first week and a dottedline may represent a second physical activity index for a second week.In FIG. 7C, on Monday (M), Tuesday (Tu), and Saturday (Sa) the secondphysical activity index of the user 112 is more than the first physicalactivity index. However, on Thursday (Th), and Friday (F) the firstphysical activity index of the user 112 was more than the physicalpositive activity index. Thus, the third emotional storyboard 714, inFIG. 7C, may assist the user 112 to analyze differences in the physicalactivities for each week and take appropriate action to improve thephysical activity index and the emotional quotient. In accordance withan embodiment, the emotional storyboard generator 208 may be configuredto generate a storyboard similar to the third emotional storyboard 714that may display calories burnt or time spent on physical activity bythe user 112 during the first week and the second week. In someembodiments, the first emotional storyboard 700, the second emotionalstoryboard 710, and the third emotional storyboard 714 may be displayedat an external apparatus or an external application, via an applicationprogramming interface (API) for content recommendation.

In accordance with an embodiment, the emotional storyboard generator 208may be further configured to set a timing goal of the physical activityand the sleep cycle for the user 112 to be achieved each day based onthe user information received from the plurality of sensors 106. Forexample, if the user information of the user 112 indicates that the user112 is overweight, the emotional storyboard generator 208 may set thetiming goal as 2 hours of running for each day to promote user's healthand well-being.

FIG. 8 illustrates an exemplary third user interface to display aregistration process of a user, in accordance with an embodiment of thedisclosure. FIG. 8 is explained in conjunction with elements from FIGS.1, 2, 3A 3B, 4, 5A, 5B, 6, and 7A to 7C. With reference to FIG. 8, thereis shown a third user interface 800. The third user interface 800 may bedisplayed on the display device 214A to register a new user with theelectronic apparatus 102. The third user interface 800 may furtherinclude a user information input UI element 802, a user image input UIelement 804, a register UI element 806, and a welcome message 808.

In operation, the user 112, may utilize I/O device 214, to provide userrelated details to the electronic apparatus 102 through the userinformation input UI element 802 and the user image input UI element804. For example, the user 112 may provide different information such asname, contact, age, and the like through the user information input UIelement 802. Further, the user 112 may click or select the user imageinput UI element 804 to upload an image stored in the memory 212. Theuser 112 may also select click or select the user image input UI element804 to click a real-time image of the user 112 using the image capturingdevice 106C. The user 112 may initiate the registration with theelectronic apparatus 102 through the selection of the register UIelement 806. The electronic apparatus 102 may be configured to connectto a social media account of the user 112 for the registration based onthe selection of the register UI element 806 by the user 112. Inaccordance with an embodiment, the electronic apparatus 102 may beconfigured to initiate the capture of the user information of the user112 (through the plurality of sensors 106) based on successfulcompletion of the registration between the user 112 and the electronicapparatus 102.

FIGS. 9A and 9B collectively depict a flowchart that illustratesexemplary operations generating an emotional storyboard and recommendingcontent or action, in accordance with an embodiment of the disclosure.With reference to FIGS. 9A and 9B, there is shown a flowchart 9. Theflowchart 900 is described in conjunction with FIGS. 1, 2, 3A, 3B, 4,5A, 5B, 6, 7A to 7C, and 8. The operations from 902 to 940 may beimplemented in the electronic apparatus 102. The operations of theflowchart 900 may start at 902 and proceed to 904.

At 904, the user information may be received from the plurality ofsensors 106 that tracks user activities of the user 112 over thespecified time period. The processor 204 may be configured to receivethe user information from the plurality of sensors 106. Examples of theuser information may include, but are not limited to, the physiologicaland non-physiological data of the user 112 such as images, biometricdata, location, height, weight, heartbeat, eye gaze, facial expression,blood-flow data, breathing intensity, body temperature, voice tone,voice volume, or head movement. The processor 204 may be furtherconfigured to store the user information in the memory 212 of theelectronic apparatus 102.

At 906, a plurality of categories of user emotions may be determinedfrom the received user information. In accordance with an embodiment,the processor 204 may be configured to determine a plurality ofdifferent categories of user emotions. Each category of user emotion ofthe plurality of categories of user emotions may correspond to one of apositive emotional type (such as happy) or a negative emotional type(such as sad).

At 908, the baseline emotion of the user 112 may be detected over afirst time period in the specified time period based on the receiveduser information and the plurality of categories of user emotions. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the baseline emotion of the user112 based on the received user information and the plurality ofcategories of user emotions. The baseline emotion may be an initialbaseline emotion which may correspond to a neutral emotion of the user112. The neutral emotion may be further updated by the electronicapparatus 102 over the first time period to obtain the actual baselineemotion of the user 112.

At 910, a plurality of intensity levels of the baseline emotion may bedetected for over the specified time period. The emotion recognition andprediction engine 206 may be configured to detect the plurality ofintensity levels of the baseline emotion based on the user informationand the received plurality of categories of user emotions (which alsoincludes different values of biometric or voice data for each category).

At 912, a threshold intensity may be set based on the detected pluralityof intensity levels of the detected baseline emotion. In accordance withan embodiment, the emotion recognition and prediction engine 206 may beconfigured to dynamically set the threshold intensity based on thedetected plurality of intensity levels.

At 914, emotional peaks in the plurality of intensity levels of thebaseline emotion may be detected based on the set threshold intensity.In accordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the emotional peaks of theplurality of intensity levels based on the set threshold intensity.Detection of the emotional peak from the plurality of intensity levelsof the baseline emotion may be described in detail, for example in FIG.3B.

At 916, a first change in the emotional characteristic of the user 112may be determined over a second time period in the specified time periodin the user information based on the detected baseline emotion. Theemotion recognition and prediction engine 206 may be configured todetermine the change in the emotional characteristic of the user 112 inthe user information based on the detected baseline emotion.Determination of the change in the emotional characteristic of the user112 may be described in detail, for example in FIGS. 3A and 4.

At 918, the dominant emotion of the user 112 may be detected based onthe detected baseline emotion, the detected emotional peaks, and thedetected change in the emotional characteristic of the user 112. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the dominant emotion based on thedetected baseline emotion, the detected emotional peaks, and thedetected change in the emotional characteristic. Detection of thedominant emotion of the user 112 may be described in detail, for examplein FIGS. 3A, 3B, and 4.

At 920, an emotional type of the dominant emotion of the user 112 may beidentified. The emotional type may be one of a positive emotional typeor a negative emotional type. In accordance with an embodiment, thedominant emotion may impact and may be used to calibrate the baselineemotion of the user 112.

At 922, triggers associated with the detected dominant emotion of theuser 112 may be identified based on the user information. The emotionrecognition and prediction engine 206 may be configured to identifytriggers associated with the detected dominant emotion of the user 112based on the user information. Examples of triggers associated with thedetected dominant emotion are described in detail, for example, in FIG.4.

At 924, the identified triggers may be correlated with the detecteddominant emotion of the user 112. The emotion recognition and predictionengine 206 may be configured to correlate the identified triggers withthe detected dominant emotion (detected change in the emotionalcharacteristic of the user 112 or detected emotional peaks). Examples ofthe correlation between the triggers and the detected dominant emotionof the user 112 are described in detail, for example, in FIG. 4.

At 926, deductive information may be generated based on an associationof the identified emotional type of the dominant emotion, the determineddominant emotion of the first user, the first change in the emotionalcharacteristic of the first user, and the detected baseline emotion. Thedeductive information may also indicate the correlation between thedetected triggers and the detected dominant emotion.

At 928, the first content or action may be identified based on aspecified emotion associated with the first content or action and thedeductive information. In accordance with an embodiment, the emotionrecognition and prediction engine 206 may be configured to identify thefirst content or action for the user 112.

At 930, an emotion which may be induced in the user 112 may be predictedbased on the identified first content or action, the user-contentpreference information, the user past emotional information , and thedetected dominant emotion of the user 112. In accordance with anembodiment, the emotion recognition and prediction engine 206 may beconfigured to predict the emotion which may be induced in the user 112based on the identified first content or action, the user-contentpreference information, the user past emotional information of the user112, and the dominant emotion as described in detail, for example inFIGS. 5A and 5B.

At 932, the identified first content or action may be retrieved. Inaccordance with an embodiment, the processor may be configured toretrieve the identified first content or the information related to theaction from the multimedia content source 110 via the communicationnetwork 104. The processor 204 may be configured to transmit the requestfor content to the multimedia content source 110 and receive the firstcontent or the information related to the action based on thetransmitted request for content. Examples of the first content mayinclude, but are not limited to, audio content, video content, imagecontent, animated content, multimedia content. Examples of the actionmay include, but are not limited to, information about anactivity-do-to, or place-to-visit.

At 934, output of the retrieved first content or action to the user 112may be controlled at least based on a specified emotion associated withthe first content or action and the generated deductive information suchthat the emotional type of the dominant emotion is inducible to thepositive emotional type from the negative emotional type. In accordancewith an embodiment, the processor 204 may be configured output theretrieved first content or the information related to the action on thedisplay device 214A for the user 112 or via an audio output device. Insome embodiments, the processor 204 may be configured to send theretrieved first content or action to the external device to render thefirst content or action to the user 112.

At 936, the emotional storyboard for the specified time period may begenerated and output to the user 112. In accordance with an embodiment,the emotional storyboard generator 208 may be configured to generate andoutput a detailed emotional storyboard for the specified time period tothe user 112. The emotional storyboard may be described in detail, forexample in FIGS. 7A to 7C.

At 938, a new dominant emotion of the user 112 may be detected based onthe output first content or action and the emotional storyboard. Inaccordance with an embodiment, the emotion recognition and predictionengine 206 may be configured to detect the new dominant emotion of theuser 112 in response to the output first content or action and theemotional storyboard. The new dominant emotion may be the emotioninduced by the recommended content or action, which may be used forfuture prediction of emotions. The new dominant emotion may becorrelated to the AE, which may then be used to accurately determine thecontent or action to be recommended.

At 940, the user-content preference information and the user pastemotional information of the user 112 may be updated based on thedetected new dominant emotion of the user 112. The processor 204 may beconfigured to update the user-content preference information and theuser past emotional information in the server 108 based on the capturednew dominant emotion captured in response to the recommended firstcontent or action. The control passes to end 942.

Various embodiments of the present disclosure may be found in a methodand an electronic apparatus (such as, the electronic apparatus 102)which includes a memory (such as, the memory 212) and circuitry (e.g.,the circuitry 202). The memory may be configured to store userinformation of a first user (such as user 112). The user information maybe received by a plurality of sensors (such as the plurality of sensors116) that tracks user activities of the first user over a specified timeperiod. The circuitry may be configured to detect a baseline emotion ofthe first user over a first time period in the specified time periodbased on the user information. The circuitry 202 may be furtherconfigured to detect a first change in an emotional characteristic ofthe first user in the user information over a second time period in thespecified time period, based on the detected baseline emotion of thefirst user. The circuitry 202 may be further configured to determine adominant emotion of the first user based on the detected baselineemotion and the detected first change in the emotional characteristic ofthe first user in the user information. The circuitry 202 may be furtherconfigured to identify an emotional type of the determined dominantemotion. The emotional type is one of a positive emotional type or anegative emotional type. The circuitry 202 may be further configured toidentify first content or action based on a specified emotion associatedwith the first content or action, the identified emotional type of thedominant emotion, the first change in the emotional characteristic ofthe first user, and the detected baseline emotion. The circuitry 202 maybe further configured to output the identified first content or actionto the first user, wherein the first content or action is output tochange the emotional type of the dominant emotion from the negativeemotional type to the positive emotional type.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to detect at least one emotional peak of the detected firstchange in the emotional characteristic of the first user based on athreshold intensity of the baseline emotion. The dominant emotion of thefirst user is determined further based on the detected at least oneemotional peak.

In accordance with an embodiment, the user information received from theplurality of sensors 106 may include at least one of physiological andnon-physiological features of the first user, and a plurality of imageframes. Each image frame of the plurality of image frames may include animage of the first user. In accordance with an embodiment, the pluralityof sensors 106 may include at least one of an imaging capturing device,an audio sensor, a biometric sensor, a heartbeat sensor, a blood-flowsensor, a motion sensor, a facial recognition sensor, or an Internet ofthings (IoT) sensor.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to generate an emotional storyboard that may include atimeline of a plurality of emotions of the first user over the specifiedof time. The plurality of emotions may include the dominant emotion andthe baseline emotion. The circuitry 202 may be further configured tooutput the generated emotional storyboard to the first user.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to correlate trigger information in the user information withthe determined dominant emotion of the first user. The triggerinformation comprises at least one of an event associated with the firstuser over the specified time period, second content visible to the firstuser at a time the plurality of sensors 106 tracks the user activitiesof the first user, and a second user associated with the first user overthe specified time period. The circuitry 202 may be further configuredto output the first content to the first user and update the generatedemotional storyboard based on the correlation of the trigger informationwith the determined dominant emotion of the first user. In accordancewith an embodiment, the emotional storyboard may include at least oneof: the user information, date time information of an occurrence of thefirst change in the emotional characteristic, trigger information forthe first change in the emotional characteristic, or the plurality ofemotions of the at least one user. In accordance with an embodiment, theemotional storyboard may further include an avatar of the first user.Virtual emotions of the avatar correspond to the plurality of emotionsof the first user.

In accordance with an embodiment, the memory may be further configuredto store user-content preference information and user past emotionalinformation of the first user. The circuitry 202 may be furtherconfigured to output at least one of video content clip or audio contentas the first content based on at least one of the stored user-contentpreference information or the stored user past emotional information ofthe at least one user. In accordance with an embodiment, the circuitry202 may be further configured to detect a second change in the emotionalcharacteristic of the at least one user based on the output firstcontent to the first user. The circuitry may be further configured toupdate the user past emotional information based on the detected secondchange in the emotional characteristic of the first user.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to predict an emotion of the first user based on theuser-content preference information and the past emotional informationof the first user. The circuitry 202 may be further configured toidentify the first content for the first user based on the predictedemotion of the first user. In accordance with an embodiment, thecircuitry may be further configured to detect a location of the firstuser and output at least one of an activity-to-do or a place-to-visit tofirst user based on the detected location.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to detect the baseline emotion and the dominant emotion ofthe first user based on a plurality of categories of user emotions. Theplurality of categories of user emotions may include at least one of asad emotion, a happy emotion, a calm emotion, an angry emotion, a fearemotion, a surprise emotion, a contempt emotion, a disgust emotion, aneutral emotion, or other variants of emotions. Each category of emotionof the plurality of categories of user emotions corresponds to one ofthe positive emotional type or the negative emotional type.

In accordance with an embodiment, the electronic apparatus iscommunicably coupled to an external apparatus that is configured tooutput the first content to the first user. The circuitry is furtherconfigured to change the first content based on the determined dominantemotion of the first user.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to receive role model information from the first user. Thecircuitry 202 may be further configured to extract, from a server,second content related to the role model information, wherein the secondcontent includes at least an image of the role model. The circuitry 202may be further configured to determine behavior of the role model in theextracted second content and recommend activity to the first user basedon the determined behavior of the role model.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to calculate a positive activity index of the first userbased on movement of the first user for the specified time period. Thecircuitry 202 may be further configured to output the calculatedpositive activity index to the first user.

In accordance with an embodiment, the electronic apparatus may be awearable device. In accordance with an embodiment, the circuitry 202 maybe further configured to detect a health status information of the firstuser based on the user information, and control output of the firstcontent to the first user based on the detected health status of thefirst user, the specified emotion associated with the first content, theidentified emotional type of the dominant emotion, the first change inthe emotional characteristic of the first user, and the detectedbaseline emotion.

In accordance with an embodiment, the circuitry 202 may be furtherconfigured to transmit a signal to an external device based on theemotional type of the dominant emotion that corresponds to the negativeemotional type. The signal may include the dominant emotion of the firstuser and a warning notification.

Various embodiments of the disclosure may provide a non-transitorycomputer readable medium and/or storage medium, and/or a non-transitorymachine readable medium and/or storage medium with a machine code and/ora set of instructions stored thereon and executable by a machine and/ora computer to provide user consumable information independent of networkconnectivity. The set of instructions in the electronic apparatus 102may cause the machine and/or computer to store user information of afirst user. The user information may be received from a plurality ofsensors that tracks user activities of the first user over a specifiedtime period. A baseline emotion of the first user may be furtherdetected over a first time period in the specified time period based onthe user information. A first change in an emotional characteristic ofthe first user may be detected in the user information over a secondtime period in the specified time period, based on the detected baselineemotion of the first user. A dominant emotion of the first user may bedetermined based on the detected baseline emotion and the detected firstchange in the emotional characteristic of the first user in the userinformation. An emotional type of the determined dominant emotion may beidentified, wherein the emotional type is one of a positive emotionaltype or a negative emotional type. Deductive information may begenerated based on an association of the identified emotional type ofthe dominant emotion, the determined dominant emotion of the first user,the first change in the emotional characteristic of the first user, andthe detected baseline emotion. Further, output of first content to thefirst user may be controlled based on a specified emotion associatedwith the first content and the generated deductive information such thatthe emotional type of the dominant emotion is inducible to the positiveemotional type from the negative emotional type.

The present disclosure may be realized in hardware, or a combination ofhardware and software. The present disclosure may be realized in acentralized fashion, in at least one computer system, or in adistributed fashion, where different elements may be spread acrossseveral interconnected computer systems. A computer system or otherapparatus adapted to carry out the methods described herein may besuited. A combination of hardware and software may be a general-purposecomputer system with a computer program that, when loaded and executed,may control the computer system such that it carries out the methodsdescribed herein. The present disclosure may be realized in hardwarethat includes a portion of an integrated circuit that also performsother functions.

The present disclosure may also be embedded in a computer programproduct, which includes all the features that enable the implementationof the methods described herein, and which when loaded in a computersystem is able to carry out these methods. Computer program, in thepresent context, means any expression, in any language, code ornotation, of a set of instructions intended to cause a system withinformation processing capability to perform a particular functioneither directly, or after either or both of the following: a) conversionto another language, code or notation; b) reproduction in a differentmaterial form.

While the present disclosure is described with reference to certainembodiments, it will be understood by those skilled in the art thatvarious changes may be made and equivalents may be substituted withoutdeparture from the scope of the present disclosure. In addition, manymodifications may be made to adapt a particular situation or material tothe teachings of the present disclosure without departure from itsscope. Therefore, it is intended that the present disclosure not belimited to the particular embodiment disclosed, but that the presentdisclosure will include all embodiments that fall within the scope ofthe appended claims.

What is claimed is:
 1. An electronic apparatus, comprising: circuitryconfigured to: detect a baseline emotion of a first user over a firsttime period in a specified time period based on user information,wherein the user information is received from a plurality of sensorsthat tracks user activities of the first user over the specified timeperiod; detect a first change in an emotional characteristic of thefirst user in the user information over a second time period in thespecified time period, based on the detected baseline emotion of thefirst user; determine a dominant emotion of the first user based on thedetected baseline emotion and the detected first change in the emotionalcharacteristic of the first user in the user information; identify anemotional type of the determined dominant emotion, wherein the emotionaltype is one of a positive emotional type or a negative emotional type;generate deductive information based on an association of the identifiedemotional type of the dominant emotion, the determined dominant emotionof the first user, the first change in the emotional characteristic ofthe first user, and the detected baseline emotion; and control output offirst content to the first user based on a specified emotion associatedwith the first content and the generated deductive information such thatthe emotional type of the dominant emotion is inducible to the positiveemotional type from the negative emotional type.
 2. The electronicapparatus according to claim 1, wherein the circuitry is furtherconfigured to detect at least one emotional peak of the detected firstchange in the emotional characteristic of the first user based on athreshold intensity of the baseline emotion, wherein the dominantemotion of the first user is determined further based on the detected atleast one emotional peak.
 3. The electronic apparatus according to claim1, wherein the user information received from the plurality of sensorscomprises at least one of: physiological and non-physiological featuresof the first user, and a plurality of image frames, wherein at least oneimage frame of the plurality of image frames comprises an image of thefirst user.
 4. The electronic apparatus according to claim 1, whereinthe plurality of sensors comprise at least one of an image capturingdevice, an audio sensor, a biometric sensor, a heartbeat sensor, ablood-flow sensor, a motion sensor, a facial recognition sensor, or anInternet of things (IOT) sensors.
 5. The electronic apparatus accordingto claim 1, wherein the circuitry is further configured to: generate anemotional storyboard that comprises a timeline of a plurality ofemotions of the first user over the specified time period, wherein theplurality of emotions comprise the dominant emotion and the baselineemotion; and output the generated emotional storyboard to the firstuser.
 6. The electronic apparatus according to claim 1, wherein thecircuitry is further configured to: correlate trigger information in theuser information with the determined dominant emotion of the first user,wherein the trigger information comprises at least one of: an eventassociated with the first user over the specified time period, secondcontent visible to the first user at a time the plurality of sensorstracks the user activities of the first user, or a second userassociated with the first user over the specified time period; andoutput the first content to the first user and update the generatedemotional storyboard based on the correlation of the trigger informationwith the determined dominant emotion of the first user.
 7. Theelectronic apparatus according to claim 6, wherein the emotionalstoryboard comprises at least one of the user information, date-timeinformation of an occurrence of the first change in the emotionalcharacteristic, the trigger information for the first change in theemotional characteristic, or the plurality of emotions of the firstuser.
 8. The electronic apparatus according to claim 7, wherein theemotional storyboard further comprises an avatar of the first user, andwherein virtual emotions of the avatar correspond to the plurality ofemotions of the first user.
 9. The electronic apparatus according toclaim 1, further comprising a memory configured to store user-contentpreference information and past emotional information of the first user,and wherein the circuitry is further configured to output at least oneof video content or audio content, as the first content, based on atleast one of the stored user-content preference information or thestored past emotional information of the first user.
 10. The electronicapparatus according to claim 9, wherein the circuitry is furtherconfigured to: detect a second change in the emotional characteristic ofthe first user based on the output first content to the first user; andupdate the past emotional information based on the detected secondchange in the emotional characteristic of the first user.
 11. Theelectronic apparatus according to claim 9, wherein the circuitry isfurther configured to: predict an emotion of the first user based on theuser-content preference information and the past emotional informationof the first user; and identify the first content for the first userbased on the predicted emotion of the first user.
 12. The electronicapparatus according to claim 1, wherein the circuitry is furtherconfigured to: detect a location of the first user; and outputinformation associated with at least one of an activity-to-do or aplace-to-visit to the first user based on the detected location.
 13. Theelectronic apparatus according to claim 1, wherein the circuitry isfurther configured to detect the baseline emotion and the dominantemotion of the first user based on a plurality of categories of useremotions, wherein the plurality of categories of user emotions compriseat least one of a sad emotion, a happy emotion, a calm emotion, an angryemotion, a fear emotion, a surprise emotion, a contempt emotion, adisgust emotion, a neutral emotion or other variants of emotions, andwherein each category of emotion of the plurality of categories of useremotions corresponds to one of the positive emotional type or thenegative emotional type.
 14. The electronic apparatus according to claim1, wherein the electronic apparatus is communicably coupled to anexternal apparatus that outputs the first content to the first user, andwherein the circuitry is further configured to change the first contentbased on the determined dominant emotion of the first user.
 15. Theelectronic apparatus according to claim 1, wherein the circuitry isfurther configured to: receive role model information from the firstuser, wherein the role model information indicates a role modelpreferred by the first user; extract, from a server, second contentrelated to the role model information, wherein the second contentincludes at least an image of the role model; determine behavior of therole model in the extracted second content; and recommend an activity tothe first user based on the determined behavior of the role model. 16.The electronic apparatus according to claim 1, wherein the circuitry isfurther configured to: calculate a positive activity index of the firstuser based on movement of the first user for the specified time period;and output the calculated positive activity index to the first user. 17.The electronic apparatus according to claim 1, wherein the electronicapparatus is a wearable device.
 18. The electronic apparatus accordingto claim 1, wherein the circuitry is further configured to: detecthealth status information of the first user based on the userinformation, and control output of the first content to the first userbased on the detected health status of the first user, the specifiedemotion associated with the first content, the identified emotional typeof the dominant emotion, the first change in the emotionalcharacteristic of the first user, and the detected baseline emotion. 19.The electronic apparatus according to claim 1, wherein the circuitry isfurther configured to transmit a signal to an external device based onthe emotional type of the dominant emotion that corresponds to thenegative emotional type, wherein the signal comprises the dominantemotion of the first user and a warning notification.
 20. A methodcomprising: in an electronic apparatus: detecting a baseline emotion ofa user over a first time period in a specified time period based on userinformation, wherein the user information is received from a pluralityof sensors that tracks user activities of the user over the specifiedtime period; detecting a change in an emotional characteristic of theuser in the user information over a second time period in the specifiedtime period based on the detected baseline emotion of the user;determining a dominant emotion of the user based on the detectedbaseline emotion and the detected change in the emotional characteristicof the user in the user information; identifying an emotional type ofthe determined dominant emotion, wherein the emotional type is one of apositive emotional type or a negative emotional type; generate deductiveinformation based on an association of the identified emotional type ofthe dominant emotion, the determined dominant emotion of the user, thechange in the emotional characteristic of the user, and the detectedbaseline emotion; and controlling output of content to the user based ona specified emotion associated with the content and the generateddeductive information such that the emotional type of the dominantemotion is inducible to the positive emotional type from the negativeemotional type.